Farmtech is a tool that aims to help the Tamilnadu farming community optimize crop production. The global demand for food greatly outstrips that for supply, and there is an urgent need for interventions to address this balance.

It is a web app that provides accurate crop recommendations based on rainfall, temperature, and other parameters. It helps farmers maximize yield by determining suitable crops. It also offers crop price prediction, enabling informed decisions on when to sell their crops to obtain maximum profit. Built with Angular, Flask, and MongoDB.

This machine learning project aims to recommend the most suitable crop to grow based on various soil and environmental factors. The model takes into account the following input data:

Predicting crop using machine learning with Random Forest, SVM, Decision Tree, Gradient Boosting, and KNN algorithms.

This Flask-based web application predicts the best crop to cultivate based on input features like Nitrogen, Phosphorus, Potassium, Temperature, Humidity, pH, and Rainfall. It loads a pre-trained machine learning model and scalers to process the input data and predicts the optimal crop based on the processed features.